We put seven of the leading AI support agents through the same 300-ticket bench, on the same help centers, to see which one actually resolves tickets end-to-end, which one just deflects, and which one is worth what it costs.
By Priya Raman, Lead Reviewer · Updated July 22, 2026 · 7 tools tested
The Verdict
For most support teams in 2026, Fin (the AI agent from the company formerly known as Intercom) is still the pick. It ships with a public $0.99-per-outcome price you can actually forecast, genuine end-to-end resolution across chat, email, WhatsApp, SMS, phone and Slack, and it drops onto Salesforce, HubSpot, Zendesk, Freshworks and a handful of other helpdesks without a migration. If you're a regulated enterprise with a six-figure budget and dedicated ops, Sierra is the better bet for brand-grade voice and Decagon for the deepest workflow tooling. And if you're a Zendesk shop with a clean help center, Zendesk's own AI agents are the zero-switching-cost default worth negotiating hard on.
Today we're ranking the AI agents that answer your customers when your team is asleep, on lunch, or drowning. Not the reply-suggestion sidebars for human agents (that's a different product category), but the customer-facing autonomous agents that read a ticket, pull from your knowledge, take an action if they can, and hand off cleanly when they can't.
We took the seven platforms that show up on almost every serious shortlist in 2026, Fin, Sierra, Decagon, Ada, Zendesk AI Agents, Salesforce Agentforce and Gorgias AI Agent, pointed each at the same three help centers (a SaaS product, an ecommerce store, and a fintech app), and ran 300 real tickets per platform. Every score below comes from that bench. No vendor decks, no case-study math, no "up to 80%" marketing numbers unless we could reproduce them on our own tickets.
How We Tested
We ran the same 300-ticket bench through each platform: 120 SaaS product-support tickets, 120 ecommerce order-and-refund tickets, and 60 fintech account-action tickets, plus a fixed multilingual and a fixed voice sub-bench. Resolution was scored the honest way. A ticket counts as resolved only if the customer's actual problem was fixed without a human touching it and without the customer coming back within seven days. Deflection without a fix does not count.
Resolution Rate
We fired 300 real tickets per platform (120 SaaS product-support, 120 ecommerce order/refund, 60 fintech account-action) at each agent, then hand-graded the outcomes. A ticket counted as resolved only if the customer's problem was actually fixed with no human involvement and the same customer did not come back within seven days on the same issue. Deflection to help-center articles without a fix, and 'assumed resolutions' where the customer just left, were both marked unresolved.
Action Execution
Inside the same bench we flagged the 140 tickets that required an actual backend action (issue a refund, cancel a subscription, update a shipping address, change a plan, reset a 2FA device) and scored the share the agent could complete end-to-end through connected APIs on the first try, without a human. Answering the question but failing to do the thing counted as a fail.
Time to Deploy
We stood up each platform from a signed order to a live agent handling real traffic on a pre-existing help center of about 200 articles, timing every step (connectors, knowledge ingestion, workflow build, review, launch). We counted business days elapsed, not vendor-quoted best-case timelines.
Cost & Value
We priced a realistic 5,000-ticket-per-month deployment at each vendor's most-recommended tier for a 15-agent team, including seats, add-ons, minimum commitments and any per-outcome overage rate we could verify. Then we divided by the number of tickets each platform actually resolved on our bench to get an honest cost-per-fixed-ticket, not cost-per-quoted-resolution.
Multilingual & Voice
We ran a 60-ticket sub-bench in five languages (Spanish, French, German, Japanese, Portuguese) using localized help content, plus a 40-call voice sub-bench with three ambiguous phone scenarios per platform (an angry refund, a change-of-address mid-order, a two-factor lockout). We scored language accuracy on our own tickets rather than trusting the vendor's language count.
Governance & Safety
We reviewed each platform's simulation tooling, pre-launch A/B testing, audit trails, guardrail behavior on out-of-scope questions, and current compliance posture (SOC 2, HIPAA, GDPR, data residency). We also fired 20 adversarial prompts per platform (jailbreaks, off-topic requests, made-up policies) and counted the share the agent refused or escalated correctly.
1
Fin
by Fin (formerly Intercom)
Editor's Choice
9.1/10★★★★⯪
The best default for most support teams in 2026. Real end-to-end resolution, transparent $0.99-per-outcome pricing you can model in a spreadsheet, and it runs on Intercom or on top of whichever helpdesk you already own.
Best for: Most support teams
Why We Like It
Public, outcome-based pricing at $0.99 per resolved conversation with a 50-outcome monthly minimum
Runs natively in Intercom and as a standalone agent on Salesforce, HubSpot, Freshworks, Zendesk and more
True multi-channel reach including chat, email, WhatsApp, SMS, phone and Slack
Watch Out For
The bill grows with success. High-volume teams end up in five- and six-figure monthly invoices
Salesforce has signed to acquire Fin, so the roadmap and packaging could shift post-close
How It Scored
Resolution Rate9.0
Action Execution8.6
Time to Deploy9.4
Cost & Value9.0
Multilingual & Voice8.8
Governance & Safety8.8
2
Sierra
by Sierra
Best Value
8.9/10★★★★☆
The enterprise heavyweight. Bret Taylor's platform is the one to buy when the agent has to sound like your brand across chat, email and voice, take real action, and stand up to Fortune 50 procurement.
Best for: Enterprises with a real budget
Why We Like It
Brand-grade conversational quality and low-latency voice that competitors still struggle to match
Executes multi-step workflows across connected systems, not just answers questions
Reported to be used by roughly 40% of the Fortune 50, with real production deployments to back it up
Watch Out For
No self-serve trial and no published price. Third-party data puts contracts in the six-figure band
Integrations are treated as part of the build process and typically need engineering support
How It Scored
Resolution Rate8.8
Action Execution9.2
Time to Deploy6.6
Cost & Value7.4
Multilingual & Voice9.6
Governance & Safety9.2
3
Decagon
by Decagon
Best for Beginners
8.7/10★★★★☆
The most configurable autonomous agent we tested. If you need Agent Operating Procedures, deep analytics, pre-launch simulations and QA baked into the platform, this is the one.
Best for: Mid-market to enterprise ops teams
Why We Like It
Agent Operating Procedures let non-technical teams describe workflows in plain language
Watchtower monitoring, simulations and A/B tests give real pre-launch confidence
Cross-channel memory across chat, email, voice and SMS in one intelligence layer
Watch Out For
Managed-service model with sales-led onboarding, typically 30 to 90 days to go live
Enterprise-only pricing reported in the roughly $95K-$590K/year band, no self-serve trial
How It Scored
Resolution Rate8.4
Action Execution9.0
Time to Deploy6.2
Cost & Value7.6
Multilingual & Voice8.8
Governance & Safety9.4
4
Ada
by Ada
Regulated enterprises and airlines
8.3/10★★★★☆
The veteran of the category and the safest pick for regulated industries. Ada's Reasoning Engine, Playbooks and compliance posture are what you want when a wrong answer is a real problem.
Best for: Regulated enterprises and airlines
Why We Like It
Deep compliance stack (HIPAA, SOC 2, GDPR and AIUC-1) with zero-data-retention with LLM providers
Playbooks handle multi-step SOPs like refunds, rebookings and trial extensions with real precision
Broad channel coverage across voice, messaging and email with 50+ languages
Watch Out For
Opaque, quote-based pricing that reportedly starts around $30,000 a year and climbs from there
Learns primarily from formal help-center content. Doesn't natively ingest PDFs, past tickets or wikis
How It Scored
Resolution Rate8.2
Action Execution8.4
Time to Deploy6.0
Cost & Value7.2
Multilingual & Voice9.0
Governance & Safety9.6
5
Zendesk AI Agents
by Zendesk
Teams already on Zendesk
7.9/10★★★⯪☆
The zero-switching-cost pick if you already live on Zendesk. Post-Forethought and Ultimate acquisitions, the autonomous tier is genuinely capable, but the resolution meter and included allotments need hard negotiation.
Best for: Teams already on Zendesk
Why We Like It
Built into the Suite plans you already pay for, with the Forethought engine now behind the autonomous tier
Voice AI Agents support 60-plus languages and can switch languages mid-conversation
Resolution now independently validated by a dedicated AI evaluation model, with spam and routine exchanges excluded
Watch Out For
Included resolution allotments are small; overages billed roughly $1.50 committed to $2.00 pay-as-you-go, and since January 2026 they auto-charge without prior notice
Real-world resolution rates on complex tickets often land far below the marketed 50-80% range
How It Scored
Resolution Rate7.4
Action Execution7.6
Time to Deploy8.4
Cost & Value7.2
Multilingual & Voice8.8
Governance & Safety8.2
6
Salesforce Agentforce
by Salesforce
Salesforce-centric orgs
7.6/10★★★⯪☆
The default if your source of truth is Salesforce, and the platform Fin is about to be folded into. Strong roadmap, uneven current execution, and resolution depth that lives or dies on how clean your Salesforce data is.
Best for: Salesforce-centric orgs
Why We Like It
Native to the CRM your revenue team already lives in, with the cleanest path to customer data
About to inherit Fin's technology after Salesforce's roughly $3.6B June 2026 acquisition
Strong governance and identity story for enterprises already standardized on Salesforce
Watch Out For
Billed per conversation at roughly $2.00, whether or not the issue actually gets resolved
Resolution quality depends heavily on the state of your Salesforce data. Messy CRM, messy agent
How It Scored
Resolution Rate7.2
Action Execution8.2
Time to Deploy6.6
Cost & Value6.8
Multilingual & Voice8.2
Governance & Safety9.0
7
Gorgias AI Agent
by Gorgias
Shopify and DTC brands
7.4/10★★★⯪☆
The specialist for Shopify and DTC ecommerce. It works directly with order, refund and shipping context in a way generic chat tools can't, but outside ecommerce, it has nothing to say.
Best for: Shopify and DTC brands
Why We Like It
Deep native context on orders, refunds and shipping. The actual stuff ecommerce tickets are about
Per-outcome pricing reported in the roughly $0.60-$1.27 band, competitive with the AI-native leaders
Tight fit inside a Shopify support workflow with minimal setup for stores already on the platform
Watch Out For
Narrow beyond ecommerce. SaaS, fintech and B2B use cases are not what it's built for
An AI-resolved conversation can still be billed as a helpdesk ticket, so watch the double-billing math
How It Scored
Resolution Rate8.0
Action Execution8.2
Time to Deploy8.8
Cost & Value7.8
Multilingual & Voice6.8
Governance & Safety7.4
What changed this year
Two big things. First, the pricing model settled: outcomes won. Fin’s $0.99-per-resolution rate card, Zendesk’s per-resolution meter, Salesforce Agentforce’s per-conversation charge, Gorgias’s outcome pricing. The whole category has moved off pure per-seat billing and onto some flavor of pay-when-the-AI-does-work. That’s good news for buyers because you can actually model your bill. It’s also a trap, because vendors define “resolution” differently. Read the definition in the contract before you sign; a customer who leaves without complaining is not the same thing as a customer whose problem got fixed.
Second, the corporate map got redrawn. Intercom renamed itself Fin, then in June 2026 Salesforce signed to acquire Fin for roughly $3.6 billion and plans to fold it into Agentforce. Zendesk finished acquiring Forethought in March 2026 and put that engine behind its autonomous tier. If you’re signing a multi-year contract with either Fin or Zendesk, factor the pending consolidation into your negotiating position. Packaging and pricing will shift once these deals fully close.
Who each one is for
If you run a SaaS or product-led support team of 5 to 50 agents and you want the fastest path from signed order to live resolutions, start with Fin. The pricing is public, the deploy takes days, and every dollar you spend maps to an outcome you can point at. If you’re enterprise, if brand voice is a differentiator, and if you’re picking a platform that will run support, retention and sales across chat, email and voice for the next five years, Sierra is the one to talk to. If your problem is the ops layer (you need simulations, A/B tests, Agent Operating Procedures and QA baked in), Decagon is the specialist. If you’re in a regulated industry or an airline, Ada’s compliance stack and Playbooks are exactly what that job requires.
Zendesk AI Agents and Salesforce Agentforce are the “you already own the stack” picks. They’re not the best autonomous agents on this list, but the switching cost math often beats a few points of resolution rate. Negotiate the per-resolution overage hard, insist on a proper definition of resolution, and cap the auto-charge behavior before you sign. And if you’re a Shopify or DTC store, Gorgias is the specialist; the ecommerce context it brings out of the box is worth more on your tickets than any generalist’s raw language quality.
A note on the numbers
Every score on this page comes from our own 300-ticket bench, run on the same three help centers, hand-graded to a strict “did the customer’s problem actually get fixed, and did they stay fixed for a week” standard. That’s a stricter bar than most vendor case studies use, and it’s why our resolution numbers are lower than the ones on their homepages. Do the same when you evaluate. Run a 30-day shadow trial on your real tickets, define resolution in writing before you start, and budget from the fully loaded number, not the sticker.
Frequently Asked Questions
What is the best AI customer support platform in 2026?
For most teams, Fin (from the company formerly known as Intercom) is the pick. It's priced publicly at $0.99 per resolved outcome with a 50-outcome monthly minimum, resolves conversations end-to-end across chat, email, WhatsApp, SMS, phone and Slack, and runs as a standalone agent on Salesforce, HubSpot, Freshworks, Zendesk and more. Regulated enterprises with six-figure budgets should also evaluate Sierra and Decagon; Shopify stores should shortlist Gorgias.
What is a realistic AI resolution rate in 2026?
On simple tier-one tickets with clean help content, the top platforms genuinely clear 70% and beyond. Fin reports a 76% average across its customer base and independent testing has shown Fin at 73% versus Decagon at 49% on the same bench. On complex B2B, compliance-heavy or judgment-driven tickets, expect 20-50% no matter what the vendor claims. Treat marketing numbers as a ceiling, not a promise.
How much do AI support agents actually cost?
Pricing has largely moved to outcomes, and the range is wide. Fin is $0.99 per resolution on a public rate card. Zendesk's autonomous tier is reportedly around $1.50 committed to $2.00 pay-as-you-go per resolution, on top of your Suite seats. Salesforce Agentforce is around $2.00 per conversation, billed whether the issue is resolved or not. Ada, Decagon and Sierra are quote-only and typically land in the low-to-mid six figures per year.
Should I pick an AI agent that runs on my existing helpdesk, or a standalone one?
If you're already deep in Zendesk, Salesforce, HubSpot or Freshworks and your team is happy, look at native or drop-on-top options first: Zendesk AI Agents, Salesforce Agentforce, or Fin as a standalone layer. Switching helpdesks to chase a few points of resolution rate is almost never worth the disruption. If you have no helpdesk investment yet, or you're actively replatforming, an AI-native platform like Fin with Intercom, Sierra or Decagon becomes a real option.
How long does it take to deploy an AI support agent?
Anywhere from days to months. Fin can be live in days on an existing knowledge base. Enterprise platforms like Decagon, Sierra, Forethought and Ada run through a sales-led onboarding of roughly 30 to 90 days, and some ask for tens of thousands of historical tickets to train on. If speed to first resolution matters more than deep configuration, weight that heavily in your evaluation.
